{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "241fcbdc-65d3-49d5-b8f9-63fe79c48bd4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fatal: destination path 'yolov5' already exists and is not an empty directory.\n",
      "/home/cll/dev/examples/yolov5/yolov5\n",
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: matplotlib>=3.2.2 in /home/cll/.local/lib/python3.10/site-packages (from -r requirements.txt (line 5)) (3.5.2)\n",
      "Requirement already satisfied: numpy>=1.18.5 in /home/cll/.local/lib/python3.10/site-packages (from -r requirements.txt (line 6)) (1.22.4)\n",
      "Requirement already satisfied: opencv-python>=4.1.1 in /home/cll/.local/lib/python3.10/site-packages (from -r requirements.txt (line 7)) (4.5.5.64)\n",
      "Requirement already satisfied: Pillow>=7.1.2 in /home/cll/.local/lib/python3.10/site-packages (from -r requirements.txt (line 8)) (9.1.1)\n",
      "Requirement already satisfied: PyYAML>=5.3.1 in /usr/lib/python3/dist-packages (from -r requirements.txt (line 9)) (5.4.1)\n",
      "Requirement already satisfied: requests>=2.23.0 in /usr/lib/python3/dist-packages (from -r requirements.txt (line 10)) (2.25.1)\n",
      "Requirement already satisfied: scipy>=1.4.1 in /home/cll/.local/lib/python3.10/site-packages (from -r requirements.txt (line 11)) (1.8.1)\n",
      "Requirement already satisfied: torch>=1.7.0 in /home/cll/.local/lib/python3.10/site-packages (from -r requirements.txt (line 12)) (1.11.0+cu113)\n",
      "Requirement already satisfied: torchvision>=0.8.1 in /home/cll/.local/lib/python3.10/site-packages (from -r requirements.txt (line 13)) (0.12.0+cu113)\n",
      "Requirement already satisfied: tqdm>=4.64.0 in /home/cll/.local/lib/python3.10/site-packages (from -r requirements.txt (line 14)) (4.64.0)\n",
      "Requirement already satisfied: protobuf<=3.20.1 in /usr/lib/python3/dist-packages (from -r requirements.txt (line 15)) (3.12.4)\n",
      "Requirement already satisfied: tensorboard>=2.4.1 in /home/cll/.local/lib/python3.10/site-packages (from -r requirements.txt (line 18)) (2.9.0)\n",
      "Requirement already satisfied: pandas>=1.1.4 in /usr/lib/python3/dist-packages (from -r requirements.txt (line 22)) (1.3.5)\n",
      "Requirement already satisfied: seaborn>=0.11.0 in /home/cll/.local/lib/python3.10/site-packages (from -r requirements.txt (line 23)) (0.11.2)\n",
      "Requirement already satisfied: ipython in /usr/lib/python3/dist-packages (from -r requirements.txt (line 37)) (7.31.1)\n",
      "Requirement already satisfied: psutil in /usr/lib/python3/dist-packages (from -r requirements.txt (line 38)) (5.9.0)\n",
      "Collecting thop>=0.1.1\n",
      "  Downloading thop-0.1.1.post2207130030-py3-none-any.whl (15 kB)\n",
      "Requirement already satisfied: packaging>=20.0 in /usr/lib/python3/dist-packages (from matplotlib>=3.2.2->-r requirements.txt (line 5)) (21.3)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/lib/python3/dist-packages (from matplotlib>=3.2.2->-r requirements.txt (line 5)) (1.3.2)\n",
      "Requirement already satisfied: pyparsing>=2.2.1 in /usr/lib/python3/dist-packages (from matplotlib>=3.2.2->-r requirements.txt (line 5)) (2.4.7)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /usr/lib/python3/dist-packages (from matplotlib>=3.2.2->-r requirements.txt (line 5)) (2.8.1)\n",
      "Requirement already satisfied: cycler>=0.10 in /usr/lib/python3/dist-packages (from matplotlib>=3.2.2->-r requirements.txt (line 5)) (0.11.0)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /usr/lib/python3/dist-packages (from matplotlib>=3.2.2->-r requirements.txt (line 5)) (4.29.1)\n",
      "Requirement already satisfied: typing-extensions in /home/cll/.local/lib/python3.10/site-packages (from torch>=1.7.0->-r requirements.txt (line 12)) (4.2.0)\n",
      "Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1->-r requirements.txt (line 18)) (1.8.1)\n",
      "Requirement already satisfied: absl-py>=0.4 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1->-r requirements.txt (line 18)) (1.0.0)\n",
      "Requirement already satisfied: grpcio>=1.24.3 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1->-r requirements.txt (line 18)) (1.46.1)\n",
      "Requirement already satisfied: werkzeug>=1.0.1 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1->-r requirements.txt (line 18)) (2.1.2)\n",
      "Requirement already satisfied: wheel>=0.26 in /usr/lib/python3/dist-packages (from tensorboard>=2.4.1->-r requirements.txt (line 18)) (0.37.1)\n",
      "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1->-r requirements.txt (line 18)) (0.4.6)\n",
      "Requirement already satisfied: markdown>=2.6.8 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1->-r requirements.txt (line 18)) (3.3.7)\n",
      "Requirement already satisfied: tensorboard-data-server<0.7.0,>=0.6.0 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1->-r requirements.txt (line 18)) (0.6.1)\n",
      "Requirement already satisfied: setuptools>=41.0.0 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1->-r requirements.txt (line 18)) (44.0.0)\n",
      "Requirement already satisfied: google-auth<3,>=1.6.3 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1->-r requirements.txt (line 18)) (2.6.6)\n",
      "Requirement already satisfied: six in /usr/lib/python3/dist-packages (from absl-py>=0.4->tensorboard>=2.4.1->-r requirements.txt (line 18)) (1.16.0)\n",
      "Requirement already satisfied: cachetools<6.0,>=2.0.0 in /home/cll/.local/lib/python3.10/site-packages (from google-auth<3,>=1.6.3->tensorboard>=2.4.1->-r requirements.txt (line 18)) (5.1.0)\n",
      "Requirement already satisfied: pyasn1-modules>=0.2.1 in /home/cll/.local/lib/python3.10/site-packages (from google-auth<3,>=1.6.3->tensorboard>=2.4.1->-r requirements.txt (line 18)) (0.2.8)\n",
      "Requirement already satisfied: rsa<5,>=3.1.4 in /home/cll/.local/lib/python3.10/site-packages (from google-auth<3,>=1.6.3->tensorboard>=2.4.1->-r requirements.txt (line 18)) (4.8)\n",
      "Requirement already satisfied: requests-oauthlib>=0.7.0 in /home/cll/.local/lib/python3.10/site-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard>=2.4.1->-r requirements.txt (line 18)) (1.3.1)\n",
      "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /home/cll/.local/lib/python3.10/site-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard>=2.4.1->-r requirements.txt (line 18)) (0.4.8)\n",
      "Requirement already satisfied: oauthlib>=3.0.0 in /usr/lib/python3/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard>=2.4.1->-r requirements.txt (line 18)) (3.2.0)\n",
      "Installing collected packages: thop\n",
      "  Attempting uninstall: thop\n",
      "    Found existing installation: thop 0.1.0.post2206102148\n",
      "    Uninstalling thop-0.1.0.post2206102148:\n",
      "      Successfully uninstalled thop-0.1.0.post2206102148\n",
      "Successfully installed thop-0.1.1.post2207130030\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "/home/cll/dev/examples/yolov5\n"
     ]
    }
   ],
   "source": [
    "!git clone https://github.com/ultralytics/yolov5\n",
    "%cd yolov5\n",
    "%pip install -r requirements.txt\n",
    "%cd -"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "61d26215-efd0-4824-8aa5-88be1c39c73c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: tqdm in /home/cll/.local/lib/python3.10/site-packages (4.64.0)\n",
      "Requirement already satisfied: datasets in /home/cll/.local/lib/python3.10/site-packages (2.3.2)\n",
      "Requirement already satisfied: wandb in /home/cll/.local/lib/python3.10/site-packages (0.12.18)\n",
      "Requirement already satisfied: joblib in /home/cll/.local/lib/python3.10/site-packages (1.1.0)\n",
      "Requirement already satisfied: dill<0.3.6 in /home/cll/.local/lib/python3.10/site-packages (from datasets) (0.3.5.1)\n",
      "Requirement already satisfied: requests>=2.19.0 in /usr/lib/python3/dist-packages (from datasets) (2.25.1)\n",
      "Requirement already satisfied: xxhash in /home/cll/.local/lib/python3.10/site-packages (from datasets) (3.0.0)\n",
      "Requirement already satisfied: multiprocess in /home/cll/.local/lib/python3.10/site-packages (from datasets) (0.70.13)\n",
      "Requirement already satisfied: packaging in /usr/lib/python3/dist-packages (from datasets) (21.3)\n",
      "Requirement already satisfied: pandas in /usr/lib/python3/dist-packages (from datasets) (1.3.5)\n",
      "Requirement already satisfied: numpy>=1.17 in /home/cll/.local/lib/python3.10/site-packages (from datasets) (1.22.4)\n",
      "Requirement already satisfied: pyarrow>=6.0.0 in /home/cll/.local/lib/python3.10/site-packages (from datasets) (8.0.0)\n",
      "Requirement already satisfied: fsspec[http]>=2021.05.0 in /home/cll/.local/lib/python3.10/site-packages (from datasets) (2022.5.0)\n",
      "Requirement already satisfied: aiohttp in /home/cll/.local/lib/python3.10/site-packages (from datasets) (3.8.1)\n",
      "Requirement already satisfied: huggingface-hub<1.0.0,>=0.1.0 in /home/cll/.local/lib/python3.10/site-packages (from datasets) (0.8.1)\n",
      "Requirement already satisfied: responses<0.19 in /home/cll/.local/lib/python3.10/site-packages (from datasets) (0.18.0)\n",
      "Requirement already satisfied: Click!=8.0.0,>=7.0 in /home/cll/.local/lib/python3.10/site-packages (from wandb) (8.0.4)\n",
      "Requirement already satisfied: GitPython>=1.0.0 in /home/cll/.local/lib/python3.10/site-packages (from wandb) (3.1.27)\n",
      "Requirement already satisfied: psutil>=5.0.0 in /usr/lib/python3/dist-packages (from wandb) (5.9.0)\n",
      "Requirement already satisfied: setproctitle in /home/cll/.local/lib/python3.10/site-packages (from wandb) (1.2.3)\n",
      "Requirement already satisfied: pathtools in /home/cll/.local/lib/python3.10/site-packages (from wandb) (0.1.2)\n",
      "Requirement already satisfied: PyYAML in /usr/lib/python3/dist-packages (from wandb) (5.4.1)\n",
      "Requirement already satisfied: promise<3,>=2.0 in /home/cll/.local/lib/python3.10/site-packages (from wandb) (2.3)\n",
      "Requirement already satisfied: shortuuid>=0.5.0 in /home/cll/.local/lib/python3.10/site-packages (from wandb) (1.0.9)\n",
      "Requirement already satisfied: protobuf<4.0dev,>=3.12.0 in /usr/lib/python3/dist-packages (from wandb) (3.12.4)\n",
      "Requirement already satisfied: setuptools in /home/cll/.local/lib/python3.10/site-packages (from wandb) (44.0.0)\n",
      "Requirement already satisfied: six>=1.13.0 in /usr/lib/python3/dist-packages (from wandb) (1.16.0)\n",
      "Requirement already satisfied: sentry-sdk>=1.0.0 in /home/cll/.local/lib/python3.10/site-packages (from wandb) (1.7.1)\n",
      "Requirement already satisfied: docker-pycreds>=0.4.0 in /home/cll/.local/lib/python3.10/site-packages (from wandb) (0.4.0)\n",
      "Requirement already satisfied: gitdb<5,>=4.0.1 in /home/cll/.local/lib/python3.10/site-packages (from GitPython>=1.0.0->wandb) (4.0.9)\n",
      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /home/cll/.local/lib/python3.10/site-packages (from huggingface-hub<1.0.0,>=0.1.0->datasets) (4.2.0)\n",
      "Requirement already satisfied: filelock in /usr/lib/python3/dist-packages (from huggingface-hub<1.0.0,>=0.1.0->datasets) (3.6.0)\n",
      "Requirement already satisfied: urllib3>=1.25.10 in /usr/lib/python3/dist-packages (from responses<0.19->datasets) (1.26.5)\n",
      "Requirement already satisfied: certifi in /usr/lib/python3/dist-packages (from sentry-sdk>=1.0.0->wandb) (2020.6.20)\n",
      "Requirement already satisfied: attrs>=17.3.0 in /usr/lib/python3/dist-packages (from aiohttp->datasets) (21.2.0)\n",
      "Requirement already satisfied: multidict<7.0,>=4.5 in /home/cll/.local/lib/python3.10/site-packages (from aiohttp->datasets) (6.0.2)\n",
      "Requirement already satisfied: charset-normalizer<3.0,>=2.0 in /home/cll/.local/lib/python3.10/site-packages (from aiohttp->datasets) (2.1.0)\n",
      "Requirement already satisfied: aiosignal>=1.1.2 in /home/cll/.local/lib/python3.10/site-packages (from aiohttp->datasets) (1.2.0)\n",
      "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /home/cll/.local/lib/python3.10/site-packages (from aiohttp->datasets) (4.0.2)\n",
      "Requirement already satisfied: yarl<2.0,>=1.0 in /home/cll/.local/lib/python3.10/site-packages (from aiohttp->datasets) (1.7.2)\n",
      "Requirement already satisfied: frozenlist>=1.1.1 in /home/cll/.local/lib/python3.10/site-packages (from aiohttp->datasets) (1.3.0)\n",
      "Requirement already satisfied: smmap<6,>=3.0.1 in /home/cll/.local/lib/python3.10/site-packages (from gitdb<5,>=4.0.1->GitPython>=1.0.0->wandb) (5.0.0)\n",
      "Requirement already satisfied: idna>=2.0 in /usr/lib/python3/dist-packages (from yarl<2.0,>=1.0->aiohttp->datasets) (3.3)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install tqdm datasets wandb joblib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2fe4f31c-3380-4ab2-928b-bf04a4ad4914",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using custom data configuration default\n",
      "Reusing dataset wider_face (/home/cll/.cache/huggingface/datasets/wider_face/default/1.0.0/b87ac8d8d65665ec6e3c2a5c6ec08d6fddb1b0f2d7f2dc3b5dcecdaf12adf22f)\n",
      "Using custom data configuration default\n",
      "Reusing dataset wider_face (/home/cll/.cache/huggingface/datasets/wider_face/default/1.0.0/b87ac8d8d65665ec6e3c2a5c6ec08d6fddb1b0f2d7f2dc3b5dcecdaf12adf22f)\n",
      "Using custom data configuration default\n",
      "Reusing dataset wider_face (/home/cll/.cache/huggingface/datasets/wider_face/default/1.0.0/b87ac8d8d65665ec6e3c2a5c6ec08d6fddb1b0f2d7f2dc3b5dcecdaf12adf22f)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Num images in wider_face training set: 12880\n",
      "Num images in wider_face val set: 3226\n",
      "Num images in wider_face test set: 16097\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 12880/12880 [01:10<00:00, 182.12it/s]\n",
      "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3226/3226 [00:17<00:00, 179.95it/s]\n",
      "100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 16097/16097 [01:28<00:00, 181.37it/s]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'yolov5/weights/yolov5l.pt'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import sys\n",
    "from pathlib import Path\n",
    "  \n",
    "from prepare_dataset import (\n",
    "    convert_to_yolov5_format, \n",
    "    create_yolov5_dataset_yaml, \n",
    "    download_dataset\n",
    ")\n",
    "from yolov5.utils.downloads import attempt_download\n",
    "\n",
    "\n",
    "(wider_face_train, wider_face_val, wider_face_test) = download_dataset(show_example=True)\n",
    "\n",
    "convert_to_yolov5_format(wider_face_train, dst_dir=Path(\"./yolov5/data/train\"))\n",
    "convert_to_yolov5_format(wider_face_val, dst_dir=Path(\"./yolov5/data/val\"))\n",
    "convert_to_yolov5_format(wider_face_test, dst_dir=Path(\"./yolov5/data/test\"))\n",
    "\n",
    "sys.path.append('yolov5')\n",
    "attempt_download('yolov5/weights/yolov5s.pt')\n",
    "attempt_download('yolov5/weights/yolov5m.pt')\n",
    "attempt_download('yolov5/weights/yolov5l.pt')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "51cae3e8-d91a-4c30-91bf-c90e7a14f748",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/cll/dev/examples/yolov5/yolov5\n"
     ]
    }
   ],
   "source": [
    "%cd yolov5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cf00468f-08fa-4003-826d-75bfb2df2d8a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/cll/.local/lib/python3.10/site-packages/torch/distributed/launch.py:178: FutureWarning: The module torch.distributed.launch is deprecated\n",
      "and will be removed in future. Use torchrun.\n",
      "Note that --use_env is set by default in torchrun.\n",
      "If your script expects `--local_rank` argument to be set, please\n",
      "change it to read from `os.environ['LOCAL_RANK']` instead. See \n",
      "https://pytorch.org/docs/stable/distributed.html#launch-utility for \n",
      "further instructions\n",
      "\n",
      "  warnings.warn(\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mcll_lambda\u001b[0m. Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mweights=weights/yolov5s.pt, cfg=, data=data/wider_face.yaml, hyp=data/hyps/hyp.scratch-low.yaml, epochs=10, batch_size=32, imgsz=768, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, noplots=False, evolve=None, bucket=, cache=None, image_weights=False, device=0, multi_scale=False, single_cls=False, optimizer=SGD, sync_bn=False, workers=8, project=runs/train, name=wider_face, exist_ok=False, quad=False, cos_lr=False, label_smoothing=0.0, patience=100, freeze=[0], save_period=-1, seed=0, local_rank=0, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest\n",
      "\u001b[34m\u001b[1mgithub: \u001b[0mup to date with https://github.com/ultralytics/yolov5 ✅\n",
      "\u001b[31m\u001b[1mrequirements:\u001b[0m tqdm>=4.64.0 not found and is required by YOLOv5, attempting auto-update...\n",
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: tqdm>=4.64.0 in /home/cll/.local/lib/python3.10/site-packages (4.64.0)\n",
      "\n",
      "\u001b[31m\u001b[1mrequirements:\u001b[0m tensorboard>=2.4.1 not found and is required by YOLOv5, attempting auto-update...\n",
      "Defaulting to user installation because normal site-packages is not writeable\n",
      "Requirement already satisfied: tensorboard>=2.4.1 in /home/cll/.local/lib/python3.10/site-packages (2.9.0)\n",
      "Requirement already satisfied: google-auth<3,>=1.6.3 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1) (2.6.6)\n",
      "Requirement already satisfied: protobuf>=3.9.2 in /usr/lib/python3/dist-packages (from tensorboard>=2.4.1) (3.12.4)\n",
      "Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1) (1.8.1)\n",
      "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1) (0.4.6)\n",
      "Requirement already satisfied: numpy>=1.12.0 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1) (1.22.4)\n",
      "Requirement already satisfied: werkzeug>=1.0.1 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1) (2.1.2)\n",
      "Requirement already satisfied: markdown>=2.6.8 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1) (3.3.7)\n",
      "Requirement already satisfied: requests<3,>=2.21.0 in /usr/lib/python3/dist-packages (from tensorboard>=2.4.1) (2.25.1)\n",
      "Requirement already satisfied: wheel>=0.26 in /usr/lib/python3/dist-packages (from tensorboard>=2.4.1) (0.37.1)\n",
      "Requirement already satisfied: grpcio>=1.24.3 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1) (1.46.1)\n",
      "Requirement already satisfied: absl-py>=0.4 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1) (1.0.0)\n",
      "Requirement already satisfied: setuptools>=41.0.0 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1) (44.0.0)\n",
      "Requirement already satisfied: tensorboard-data-server<0.7.0,>=0.6.0 in /home/cll/.local/lib/python3.10/site-packages (from tensorboard>=2.4.1) (0.6.1)\n",
      "Requirement already satisfied: six in /usr/lib/python3/dist-packages (from absl-py>=0.4->tensorboard>=2.4.1) (1.16.0)\n",
      "Requirement already satisfied: pyasn1-modules>=0.2.1 in /home/cll/.local/lib/python3.10/site-packages (from google-auth<3,>=1.6.3->tensorboard>=2.4.1) (0.2.8)\n",
      "Requirement already satisfied: cachetools<6.0,>=2.0.0 in /home/cll/.local/lib/python3.10/site-packages (from google-auth<3,>=1.6.3->tensorboard>=2.4.1) (5.1.0)\n",
      "Requirement already satisfied: rsa<5,>=3.1.4 in /home/cll/.local/lib/python3.10/site-packages (from google-auth<3,>=1.6.3->tensorboard>=2.4.1) (4.8)\n",
      "Requirement already satisfied: requests-oauthlib>=0.7.0 in /home/cll/.local/lib/python3.10/site-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard>=2.4.1) (1.3.1)\n",
      "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /home/cll/.local/lib/python3.10/site-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard>=2.4.1) (0.4.8)\n",
      "Requirement already satisfied: oauthlib>=3.0.0 in /usr/lib/python3/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard>=2.4.1) (3.2.0)\n",
      "\n",
      "\u001b[31m\u001b[1mrequirements:\u001b[0m 2 packages updated per /home/cll/dev/examples/yolov5/yolov5/requirements.txt\n",
      "\u001b[31m\u001b[1mrequirements:\u001b[0m ⚠️ \u001b[1mRestart runtime or rerun command for updates to take effect\u001b[0m\n",
      "\n",
      "YOLOv5 🚀 v6.1-325-g3e85863 Python-3.10.4 torch-1.11.0+cu113 CUDA:0 (NVIDIA RTX A6000, 48685MiB)\n",
      "\n",
      "Added key: store_based_barrier_key:1 to store for rank: 0\n",
      "Rank 0: Completed store-based barrier for key:store_based_barrier_key:1 with 1 nodes.\n",
      "\u001b[34m\u001b[1mhyperparameters: \u001b[0mlr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=0.05, cls=0.5, cls_pw=1.0, obj=1.0, obj_pw=1.0, iou_t=0.2, anchor_t=4.0, fl_gamma=0.0, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, mosaic=1.0, mixup=0.0, copy_paste=0.0\n",
      "\u001b[34m\u001b[1mTensorBoard: \u001b[0mStart with 'tensorboard --logdir runs/train', view at http://localhost:6006/\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m: wandb version 0.12.21 is available!  To upgrade, please run:\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m:  $ pip install wandb --upgrade\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.12.18\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in \u001b[35m\u001b[1m/home/cll/dev/examples/yolov5/yolov5/wandb/run-20220727_125348-ho9wuu87\u001b[0m\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m: Run \u001b[1m`wandb offline`\u001b[0m to turn off syncing.\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33mwider_face\u001b[0m\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/cll_lambda/YOLOv5\u001b[0m\n",
      "\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/cll_lambda/YOLOv5/runs/ho9wuu87\u001b[0m\n",
      "YOLOv5 temporarily requires wandb version 0.12.10 or below. Some features may not work as expected.\n",
      "Overriding model.yaml nc=80 with nc=1\n",
      "\n",
      "                 from  n    params  module                                  arguments                     \n",
      "  0                -1  1      3520  models.common.Conv                      [3, 32, 6, 2, 2]              \n",
      "  1                -1  1     18560  models.common.Conv                      [32, 64, 3, 2]                \n",
      "  2                -1  1     18816  models.common.C3                        [64, 64, 1]                   \n",
      "  3                -1  1     73984  models.common.Conv                      [64, 128, 3, 2]               \n",
      "  4                -1  2    115712  models.common.C3                        [128, 128, 2]                 \n",
      "  5                -1  1    295424  models.common.Conv                      [128, 256, 3, 2]              \n",
      "  6                -1  3    625152  models.common.C3                        [256, 256, 3]                 \n",
      "  7                -1  1   1180672  models.common.Conv                      [256, 512, 3, 2]              \n",
      "  8                -1  1   1182720  models.common.C3                        [512, 512, 1]                 \n",
      "  9                -1  1    656896  models.common.SPPF                      [512, 512, 5]                 \n",
      " 10                -1  1    131584  models.common.Conv                      [512, 256, 1, 1]              \n",
      " 11                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          \n",
      " 12           [-1, 6]  1         0  models.common.Concat                    [1]                           \n",
      " 13                -1  1    361984  models.common.C3                        [512, 256, 1, False]          \n",
      " 14                -1  1     33024  models.common.Conv                      [256, 128, 1, 1]              \n",
      " 15                -1  1         0  torch.nn.modules.upsampling.Upsample    [None, 2, 'nearest']          \n",
      " 16           [-1, 4]  1         0  models.common.Concat                    [1]                           \n",
      " 17                -1  1     90880  models.common.C3                        [256, 128, 1, False]          \n",
      " 18                -1  1    147712  models.common.Conv                      [128, 128, 3, 2]              \n",
      " 19          [-1, 14]  1         0  models.common.Concat                    [1]                           \n",
      " 20                -1  1    296448  models.common.C3                        [256, 256, 1, False]          \n",
      " 21                -1  1    590336  models.common.Conv                      [256, 256, 3, 2]              \n",
      " 22          [-1, 10]  1         0  models.common.Concat                    [1]                           \n",
      " 23                -1  1   1182720  models.common.C3                        [512, 512, 1, False]          \n",
      " 24      [17, 20, 23]  1     16182  models.yolo.Detect                      [1, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [128, 256, 512]]\n",
      "Model summary: 270 layers, 7022326 parameters, 7022326 gradients, 15.9 GFLOPs\n",
      "\n",
      "Transferred 343/349 items from weights/yolov5s.pt\n",
      "\u001b[34m\u001b[1mAMP: \u001b[0mchecks passed ✅\n",
      "Scaled weight_decay = 0.0005\n",
      "\u001b[34m\u001b[1moptimizer:\u001b[0m SGD with parameter groups 57 weight (no decay), 60 weight, 60 bias\n",
      "\u001b[34m\u001b[1malbumentations: \u001b[0mBlur(always_apply=False, p=0.01, blur_limit=(3, 7)), MedianBlur(always_apply=False, p=0.01, blur_limit=(3, 7)), ToGray(always_apply=False, p=0.01), CLAHE(always_apply=False, p=0.01, clip_limit=(1, 4.0), tile_grid_size=(8, 8))\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mScanning '/home/cll/dev/examples/yolov5/yolov5/data/train/labels' images \u001b[0m\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING: /home/cll/dev/examples/yolov5/yolov5/data/train/images/10969.png: ignoring corrupt image/label: non-normalized or out of bounds coordinates [     1.0254]\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING: /home/cll/dev/examples/yolov5/yolov5/data/train/images/12381.png: 1 duplicate labels removed\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING: /home/cll/dev/examples/yolov5/yolov5/data/train/images/3232.png: 1 duplicate labels removed\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mWARNING: /home/cll/dev/examples/yolov5/yolov5/data/train/images/7207.png: 1 duplicate labels removed\n",
      "\u001b[34m\u001b[1mtrain: \u001b[0mNew cache created: /home/cll/dev/examples/yolov5/yolov5/data/train/labels.cache\n",
      "\u001b[34m\u001b[1mval: \u001b[0mScanning '/home/cll/dev/examples/yolov5/yolov5/data/val/labels' images and \u001b[0m\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING: /home/cll/dev/examples/yolov5/yolov5/data/val/images/1060.png: 1 duplicate labels removed\n",
      "\u001b[34m\u001b[1mval: \u001b[0mWARNING: /home/cll/dev/examples/yolov5/yolov5/data/val/images/1885.png: ignoring corrupt image/label: non-normalized or out of bounds coordinates [      1.002]\n",
      "\u001b[34m\u001b[1mval: \u001b[0mNew cache created: /home/cll/dev/examples/yolov5/yolov5/data/val/labels.cache\n",
      "Plotting labels to runs/train/wider_face5/labels.jpg... \n",
      "\n",
      "\u001b[34m\u001b[1mAutoAnchor: \u001b[0m3.55 anchors/target, 0.984 Best Possible Recall (BPR). Current anchors are a good fit to dataset ✅\n",
      "Image sizes 768 train, 768 val\n",
      "Using 8 dataloader workers\n",
      "Logging results to \u001b[1mruns/train/wider_face5\u001b[0m\n",
      "Starting training for 10 epochs...\n",
      "\n",
      "     Epoch   gpu_mem       box       obj       cls    labels  img_size\n",
      "       0/9     10.9G    0.1237   0.06715         0       777       768:   0%|   Reducer buckets have been rebuilt in this iteration.\n",
      "       0/9     10.9G    0.1038   0.06283         0       760       768:  29%|██▉^C\n",
      "WARNING:torch.distributed.elastic.agent.server.api:Received 2 death signal, shutting down workers\n",
      "WARNING:torch.distributed.elastic.multiprocessing.api:Sending process 33606 closing signal SIGINT\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/tqdm/std.py\", line 1195, in __iter__\n",
      "    for obj in iterable:\n",
      "  File \"/home/cll/dev/examples/yolov5/yolov5/utils/dataloaders.py\", line 167, in __iter__\n",
      "    yield next(self.iterator)\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/torch/utils/data/dataloader.py\", line 530, in __next__\n",
      "    data = self._next_data()\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/torch/utils/data/dataloader.py\", line 1207, in _next_data\n",
      "    idx, data = self._get_data()\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/torch/utils/data/dataloader.py\", line 1163, in _get_data\n",
      "    success, data = self._try_get_data()\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/torch/utils/data/dataloader.py\", line 1011, in _try_get_data\n",
      "    data = self._data_queue.get(timeout=timeout)\n",
      "  File \"/usr/lib/python3.10/queue.py\", line 180, in get\n",
      "    self.not_empty.wait(remaining)\n",
      "  File \"/usr/lib/python3.10/threading.py\", line 324, in wait\n",
      "    gotit = waiter.acquire(True, timeout)\n",
      "KeyboardInterrupt\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/cll/dev/examples/yolov5/yolov5/train.py\", line 642, in <module>\n",
      "    main(opt)\n",
      "  File \"/home/cll/dev/examples/yolov5/yolov5/train.py\", line 537, in main\n",
      "    train(opt.hyp, opt, device, callbacks)\n",
      "  File \"/home/cll/dev/examples/yolov5/yolov5/train.py\", line 301, in train\n",
      "    for i, (imgs, targets, paths, _) in pbar:  # batch -------------------------------------------------------------\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/tqdm/std.py\", line 1210, in __iter__\n",
      "    self.close()\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/tqdm/std.py\", line 1316, in close\n",
      "    self.display(pos=0)\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/tqdm/std.py\", line 1509, in display\n",
      "    self.sp(self.__str__() if msg is None else msg)\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/tqdm/std.py\", line 1165, in __str__\n",
      "    return self.format_meter(**self.format_dict)\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/tqdm/std.py\", line 539, in format_meter\n",
      "    res = bar_format.format(bar=full_bar, **format_dict)\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/tqdm/std.py\", line 188, in __format__\n",
      "    def __format__(self, format_spec):\n",
      "KeyboardInterrupt\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/tqdm/std.py\", line 1195, in __iter__\n",
      "    for obj in iterable:\n",
      "  File \"/home/cll/dev/examples/yolov5/yolov5/utils/dataloaders.py\", line 167, in __iter__\n",
      "    yield next(self.iterator)\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/torch/utils/data/dataloader.py\", line 530, in __next__\n",
      "    data = self._next_data()\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/torch/utils/data/dataloader.py\", line 1207, in _next_data\n",
      "    idx, data = self._get_data()\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/torch/utils/data/dataloader.py\", line 1163, in _get_data\n",
      "    success, data = self._try_get_data()\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/torch/utils/data/dataloader.py\", line 1011, in _try_get_data\n",
      "    data = self._data_queue.get(timeout=timeout)\n",
      "  File \"/usr/lib/python3.10/queue.py\", line 180, in get\n",
      "    self.not_empty.wait(remaining)\n",
      "  File \"/usr/lib/python3.10/threading.py\", line 324, in wait\n",
      "    gotit = waiter.acquire(True, timeout)\n",
      "KeyboardInterrupt\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"/home/cll/dev/examples/yolov5/yolov5/train.py\", line 642, in <module>\n",
      "    main(opt)\n",
      "  File \"/home/cll/dev/examples/yolov5/yolov5/train.py\", line 537, in main\n",
      "    train(opt.hyp, opt, device, callbacks)\n",
      "  File \"/home/cll/dev/examples/yolov5/yolov5/train.py\", line 301, in train\n",
      "    for i, (imgs, targets, paths, _) in pbar:  # batch -------------------------------------------------------------\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/tqdm/std.py\", line 1210, in __iter__\n",
      "    self.close()\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/tqdm/std.py\", line 1316, in close\n",
      "    self.display(pos=0)\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/tqdm/std.py\", line 1509, in display\n",
      "    self.sp(self.__str__() if msg is None else msg)\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/tqdm/std.py\", line 1165, in __str__\n",
      "    return self.format_meter(**self.format_dict)\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/tqdm/std.py\", line 539, in format_meter\n",
      "    res = bar_format.format(bar=full_bar, **format_dict)\n",
      "  File \"/home/cll/.local/lib/python3.10/site-packages/tqdm/std.py\", line 188, in __format__\n",
      "    def __format__(self, format_spec):\n",
      "KeyboardInterrupt\n"
     ]
    }
   ],
   "source": [
    "!python -m torch.distributed.launch --nproc_per_node 2 train.py --data data/wider_face.yaml --batch-size 64 --epochs 10 --img-size 768 --project runs/train --name wider_face --weights weights/yolov5s.pt --device 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0cfd4806-07af-4acf-86e1-fd44097a2143",
   "metadata": {},
   "outputs": [],
   "source": [
    "!python -m torch.distributed.launch --nproc_per_node 2 train.py --data data/wider_face.yaml --batch-size 64 --epochs 10 --img-size 768 --project runs/train --name wider_face --weights weights/yolov5m.pt --device 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3f01d37e-e61c-4fe3-980b-6414e2018f58",
   "metadata": {},
   "outputs": [],
   "source": [
    "!python -m torch.distributed.launch --nproc_per_node 2 train.py --data data/wider_face.yaml --batch-size 64 --epochs 10 --img-size 768 --project runs/train --name wider_face --weights weights/yolov5l.pt --device 0"
   ]
  }
 ],
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